Two high-impact extreme precipitation events during the Meiyu season: simulations and their sensitivity to a scale-aware convective parameterization scheme

Abstract

Abstract In this study, we investigate the impact of a scale-aware convective parameterization scheme (CPS) on simulating two high-impact extreme precipitation events during the Meiyu season at a 1 km resolution. Compared with explicit resolving simulation, applying scale-aware CPS mostly affects the atmospheric environment before convection is triggered and the regions outside the convective cell (e.g., stratiform regions) by consuming convective available potential energy (CAPE), which further inhibits precipitation. For the 2019 event, since the explicit resolving simulation underestimates precipitation, applying scale-aware CPS further inhibits precipitation and reduces the skill for the heavy rainfall category. In contrast, for the 2020 event, as the explicit resolving simulation overestimates precipitation, using scale-aware CPS inhibits precipitation and improves the skill of the model. When scale-aware CPS is applied, increasing σ 1 , which represents the effect of horizontal resolution, the CPS precipitation is reduced and the grid-scale precipitation is increased, but the overall effect inhibits the total precipitation. However, with the increase in σ 1 , although the number of stations with heavy rainfall (≥50 mm) is reduced, the average precipitation among these stations is increased. Further analysis of those stations with the largest 24 h precipitation and cross sections over regions with large radar reflectivity shows that increasing σ 1 reduces the CAPE consumed by CPS and provides a more favorable environment for strong convections and strengthens precipitation. The results of this study may provide useful information for operational model application and may be beneficial to society.